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production-cwv-review

Use when comparing real-user field performance data (CrUX/RUM) against lab Lighthouse data to find divergences where pages score well in the lab but are slow for real users. NOT a replacement for the Lighthouse/lab baseline, NOT for setting up RUM/analytics from scratch, NOT for synthetic load/stress testing.

68

Quality

85%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

75%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-structured four-phase workflow with a concrete API endpoint, exact p75 thresholds, a comparison table template, explicit stop conditions, and a fallback path. The gaps are minor: the intro duplicates the description's premise, no example CrUX request payload is given, and partial-data cases plus content splitting into references go unaddressed.

Suggestions

Trim or fold the opening paragraph into a single goal line — it re-explains the lab-vs-field premise the description already states.

Add a copy-paste example CrUX records:queryRecord request (curl with JSON body for one origin/URL) so Phase 0 is fully executable without recalling the API shape.

Address partial-data checkpoints in the workflow, e.g., what to do when origin-level CrUX data exists but URL-level data is missing.

Consider moving the CrUX API query details or the Phase 2 divergence-cause catalog into a one-level-deep reference file to keep SKILL.md a lean overview.

DimensionReasoningScore

Conciseness

Mostly efficient — the Phase 2 divergence causes are genuinely non-obvious domain knowledge that earns its tokens — but the 3-sentence opening paragraph ('Lighthouse measures one page load, once...') restates the description's premise and could be trimmed, and parenthetical justifications ('matching Google's own "Good" threshold methodology') are mildly padded.

4 / 5

Actionability

Concrete guidance includes the actual CrUX endpoint URL, the API-key/PSI-fallback path, named RUM sources to check (GA4 Web Vitals event, Cloudflare, Sentry, Datadog), exact p75 thresholds (<2.5s, <200ms, <0.1), and a comparison table template. The minor gap is that no example API request payload (curl or JSON body) is shown, so the Phase 0 data pull is not fully copy-paste ready.

4 / 5

Workflow Clarity

Phases 0–3 are clearly sequenced with real checkpoints — 'that absence IS the Phase 3 finding. Stop here rather than fabricating', the PSI fallback when no API key exists, and 'If field is *better* than lab, note it and move on'. Not a destructive/batch operation so no validation cap applies; remaining gaps are minor (e.g., handling origin-level CrUX data when URL-level data is missing).

4 / 5

Progressive Disclosure

No bundle files exist and none are strictly needed; sections are well-organized and external skill pointers ('load-test-bootstrap', 'third-party-script-audit') are clearly signaled. At ~82 lines it exceeds the under-50-line simple-skill exception for a top score, and material like the CrUX API query details or the divergence-cause list could plausibly live in a one-level-deep reference file.

4 / 5

Total

16

/

20

Passed

Description

87%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description with an explicit 'Use when' trigger, concrete data-source keywords, and three NOT-for boundaries that sharply delimit scope against neighboring skills. Its main gaps are the absent 'Core Web Vitals' / metric-name trigger phrases a user would most naturally say, and capability coverage limited to the comparison itself rather than the full audit output.

DimensionReasoningScore

Specificity

The description names concrete data sources ('real-user field performance data (CrUX/RUM) against lab Lighthouse data') and the core action ('comparing... to find divergences where pages score well in the lab but are slow for real users'), but the downstream outputs (comparison table, divergence diagnosis, findings) are not listed, leaving minor gaps in coverage.

4 / 5

Completeness

An explicit 'Use when comparing real-user field performance data (CrUX/RUM) against lab Lighthouse data' trigger answers 'when' with a concrete phrase that simultaneously states what the skill does, and three 'NOT for...' clauses add further when-not guidance — both what and when are explicit.

5 / 5

Trigger Term Quality

Good keyword coverage with natural terms users would say — 'CrUX', 'RUM', 'Lighthouse', 'field', 'lab', 'real users' — but common variations like 'Core Web Vitals', 'LCP/INP/CLS', and 'PageSpeed' are missing, so a few natural terms are absent.

4 / 5

Distinctiveness Conflict Risk

A clear niche (field-vs-lab performance divergence) with distinct triggers, plus explicit exclusions ('NOT a replacement for the Lighthouse/lab baseline, NOT for setting up RUM/analytics from scratch, NOT for synthetic load/stress testing') that disambiguate adjacent skills — minimal conflict risk.

5 / 5

Total

18

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

vannifr/agent-skills

Path

skills/production-cwv-review/SKILL.md

Reviewed

Table of Contents

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